• IMMUNE NETWORK
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• v.21 no.1
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• pp.3.1-3.16
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• 2021

Coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been spreading worldwide since its outbreak in December 2019, and World Health Organization declared it as a pandemic on March 11, 2020. SARS-CoV-2 is highly contagious and is transmitted through airway epithelial cells as the first gateway. SARS-CoV-2 is detected by nasopharyngeal or oropharyngeal swab samples, and the viral load is significantly high in the upper respiratory tract. The host cellular receptors in airway epithelial cells, including angiotensin-converting enzyme 2 and transmembrane serine protease 2, have been identified by single-cell RNA sequencing or immunostaining. The expression levels of these molecules vary by type, function, and location of airway epithelial cells, such as ciliated cells, secretory cells, olfactory epithelial cells, and alveolar epithelial cells, as well as differ from host to host depending on age, sex, or comorbid diseases. Infected airway epithelial cells by SARS-CoV-2 in ex vivo experiments produce chemokines and cytokines to recruit inflammatory cells to target organs. Same as other viral infections, IFN signaling is a critical pathway for host defense. Various studies are underway to confirm the pathophysiological mechanisms of SARS-CoV-2 infection. Herein, we review cellular entry, host-viral interactions, immune responses to SARS-CoV-2 in airway epithelial cells. We also discuss therapeutic options related to epithelial immune reactions to SARS-CoV-2.

• Journal of Distribution Science
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• v.22 no.7
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• pp.107-117
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• 2024

Purpose: Consumers have become more interested in eating organic food in recent decades because of the effect of merchants' advertising. Eating organic food is also shown to strengthen immunity, especially during the recent COVID-19 pandemic. However, consumers may find it more difficult to choose organic food retailers than to purchase conventional goods. This is because of the uncertainty characterizing the process of selecting organic food retailers, despite the growing rivalry across supermarket chains that sell organic goods. This study explores how consumers' perceived image (social responsibility and ability image) of organic food stores affects consumer loyalty. Research design, data and methodology: The data for the analysis were collected using Macromill Embrain, an online research service agency. The data were analyzed using SPSS 26 and Smart PLS 4.0. Results: Based on structural equation modeling, the findings of the study demonstrate that store image positively impactsstore loyalty, and that the mediator (perceived value) affects the relationship between the two variables. Conclusions: Organic food stores must understand consumers to improve store loyalty. Efforts such as providing a user community that enables joint behavior by sharing experiences among customers or launching campaigns to improve consumers' perceived brand identity can increase store loyalty.

• Journal of Distribution Science
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• v.22 no.7
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• pp.95-106
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• 2024

Purpose: This study explores the effect on supply chain agility and logistics performance of building mutual trust between manufacturing companies that have adopted supply chain management. Previous studies have categorized trust into affective and cognitive types, and speed, flexibility, and responsiveness are recognized as subfactors of supply chain agility. Methodology: A survey gathered responses from employees of domestic manufacturing firms with supply chain management implementations. 254 valid responses underwent statistical analysis using structural equation modeling (SPSS 23.0 and AMOS 23.0). Results: Affective trust positively influences speed and responsiveness but not flexibility. Cognitive trust positively affects speed, flexibility, and responsiveness. Supply chain agility positively impacts logistics performance. However, neither affective nor cognitive trust significantly influences logistics performance. Conclusions: The study suggests that cognitive trust based on capabilities is more important than affective trust for flexibility in corporate relationships, a subfactor of supply chain agility. However, trust alone cannot enhance corporate performance. This research is significant as it examines the roles of trust and agility in the context of the COVID-19 pandemic, which has exacerbated the manufacturing business environment.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.2
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• pp.75-89
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• 2024

The demand for metaverse is increasing rapidly due to the development of 3D information technology and the pandemic situation caused by COVID-19. Small and medium-sized enterprises(SMEs) are also in increasing demand for metaverse in the community, meetings, and customer services of their employees. Based on the UTAUT model, this study investigated the acceptance of the Metaverse-type information system(IS) by employees of SMEs. Using the responses from 170 SMEs employees, we conducted the regression analyses SMEs employees' usage intention on Metaverse-type IS. The results of the research analyses were as follows. First, among the variables of the UTAUT model, performance expectations, social influence, and promotion conditions had a significant effect on the intention to use. Second, among the variables derived from the industrial specificity of Metaverse-type IS, only individual innovation had a significant influence on the intention to use. Last but not least, in the relationship between the intention to use Metaverse-type IS and the influencing factors, only individual innovation was significant in the moderating effect according to past metaverse use experience.

• Journal of Practical Engineering Education
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• v.16 no.3_spc
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• pp.267-274
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• 2024

One challenge with teaching practical programming classes is the standardization of development tools on student computers. This is particularly true when a complicated setup process is required before beginning to code, or in remote classes, such as those necessitated by the COVID-19 pandemic, where the instructor cannot provide individual troubleshooting assistance. In such cases, students who encounter problems during the setup process may give up on the class altogether before even beginning to code. Therefore, this paper recommends using GitHub Codespaces as a tool for implementing standardized student development environments from day one. Codespaces provides Docker containers that an instructor can configure in such a way as to enable students to practice installing various coding tools within a controlled space, while also providing a language-specific, fully optimized development environment. In addition, Codespaces may be used more effectively in collaboration with GitHub Classroom, which helps instructors manage both the starter code and coding environment in which students work. In this paper, we compare two semesters of university Node.JS programming classes that utilized different development environments: one localized on student computers, the other containerized in Codespaces online. Then, we discuss how GitHub Codespaces and GitHub Classroom can be used to increase the effectiveness of practical programming classes while also increasing student engagement and programming confidence in class.

• Journal of Information Processing Systems
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• v.20 no.1
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• pp.93-104
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• 2024

China is playing more predominant role in the liquefied natural gas (LNG) market worldwide and LNG import price is subject to various factors both at home and abroad. Nevertheless, previous studies rarely heed a multiple of factors. A time-varying parameter factor augmented vector auto-regression (TVP-FAVAR) model is adopted to discover the determinants of China's LNG import price and their dynamic impacts from January 2012 to December 2021. According to the findings, market fundamentals have a greater impact on the import price of natural gas in China than overall economic demand, financial considerations, and world oil prices. The primary determinants include domestic gas consumption, consumer confidence and other demand-side information. Then, there are diverse and time-varying spillover effects of the four common determinants on the volatility of China's LNG import price at different intervals and time nodes. The price volatility is more sensitive and long-lasting to domestic natural gas pricing reform than other negative shocks such as the Sino-US trade war and the COVID-19 pandemic. The results in this study further proves the importance of domestic natural gas market liberalization. China ought to do more to support the further marketization of natural gas prices while working harder to guarantee natural gas supplies.

• Journal of Distribution Science
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• v.22 no.8
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• pp.37-53
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• 2024

Purpose: Global warming is increasingly aggravated by environmental degradation, a challenge that can be mitigated through strategic logistic policies. This study introduces the dynamics of green trade in environmental goods for the Organisation of Islamic Cooperation (OIC) nations. It is a region known for its high environmental degradation, political risk and instability. This study examines how technological innovation and political factors influence the geographic distribution of green trade among OIC nations from 1994 to 2021 using the structural gravity model. The COVID-19 pandemic further emphasised the need for resilient and eco-friendly approaches. Research design, data and methodology: The main objective of the study is to analyse the impact of technological innovation along with scrutinising political determinants of green trade in the OIC region from 1994 to 2021 using the structural gravity model. Results: The results reveal geographic proximity, RTA, and innovation significantly boost green trade. Similarly, OIC's green trade performance has been impeded by high political risk and instability. Conclusions: The research recommends fostering political stability, and conducting further research using longitudinal studies and machine learning to strengthen the understanding of innovation and green trade in the OIC. This will inform policies for sustainable economic growth through green trade.

• Journal of Dairy Science and Biotechnology
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• v.42 no.1
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• pp.1-8
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• 2024

The global dairy industry has faced substantial challenges because of the prolonged coronavirus of 2019 (COVID-19) pandemic since 2020 and the initiation of conflict between the Ukraine and Russia. In 2022, the overall milk production reached 936 million tons, reflecting a modest 1.1% increase in total global production. This indicates below-average growth for the second consecutive year because the supply to major export regions became more challenging owing to a significant increase in costs. In China, India, and Pakistan, total milk production increased markedly by 3.1% (average) because of buffalo milk production. In the near future, global milk production is expected to exhibit an average annual growth rate of 1.5%, exceeding that of other major agricultural products. Notably, the trade flow of dairy products is highly reactive to changes in the trade policy environment. Revisions to existing trade agreements or the introduction of new agreements can significantly impact the demand for dairy products and alter the trade patterns of the industry. Collectively, adaptability and strategic policy responses are critical in shaping the future development of this industry, and industry stakeholders worldwide should remain vigilant and prepare for these challenges.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2564-2588
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• 2024

Due to COVID19 pandemic, most of educational institutions and schools changed the traditional way of teaching to online teaching and learning using well-known Learning Management Systems (LMS) such as Moodle, Canvas, Blackboard, etc. Accordingly, LMS started to generate a large data related to students' characteristics and achievements and other course-related information. This makes it difficult to teachers to monitor students' behaviour and performance. Therefore, a need to support teachers with a tool alerting student who might be in risk based on their recorded activities and achievements in adopted LMS in the school. This paper focuses on the benefits of using recorded data in LMS platforms, specifically Moodle, to predict students' performance by analysing their behavioural data and engagement activities using data mining techniques. As part of the overall process, this study encountered the task of extracting and selecting relevant data features for predicting performance, along with designing the framework and choosing appropriate machine learning techniques. The collected data underwent pre-processing operations to remove random partitions, empty values, duplicates, and code the data. Different machine learning techniques, including k-NN, TREE, Ensembled Tree, SVM, and MLPNNs were applied to the processed data. The results showed that the MLPNNs technique outperformed other classification techniques, achieving a classification accuracy of 93%, while SVM and k-NN achieved 90% and 87% respectively. This indicates the possibility for future research to investigate incorporating other neural network methods for categorizing students using data from LMS.

• Research in Mathematical Education
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• v.27 no.3
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• pp.253-265
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• 2024

This editorial explores the transformative potential of technology in advancing equitable teaching and learning in mathematics education. The COVID-19 pandemic has underscored the need for innovative approaches to education, particularly in leveraging technology to create more inclusive and effective learning environments. This special issue focuses on how emerging technologies can deepen students' mathematical proficiencies, shape students' identities, and promote equitable teaching practices. The EqT-tech framework is introduced, highlighting six key dimensions that enhance equitable mathematics education through technology: inquiry-based learning, mathematical identity and agency, formative assessment, collaborative learning, amplification of cognitive processes, and insights into social justice issues. Through a review of seven manuscripts, three recurring themes are identified: the use of technology to develop students' mathematical identity and agency, the role of collaborative platforms in enhancing collective learning, and the expanding nature of emergent technology to increase mathematical rigor as well as awareness for teaching mathematics for social justice exploring inequities within our communities. These studies imply an emphasis on the importance of task design and teacher knowledge in implementing equitable teaching practices, suggesting that technology, when used thoughtfully, can significantly advance equity in mathematics education.